Microbial polyhydroxyalkanoate synthesis from field pea starch hydrolysate
Why this work is in the frame
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Bibliographic record
Abstract
Significant growth is anticipated in the plant-based protein industry over the next five years. To ensure sector viability into the future, development of value-added applications for starchy by-products from pulse crops such as field peas is essential. This study demonstrates utilization of field pea starch — more crystalline than other starches — as an inexpensive carbon source for microbial poly(3-hydroxyalkanoate) (PHA) biopolymer production. Commercial enzymes typically used for cereal starches (Stargen and a cocktail of Stargen, Optimash, GC626) generated sugar hydrolysates with similar glucose content (~80 g L −1 ) from 10 % (w v −1 ) crude pea starch. When used as a carbon source for PHA biosynthesis in several strains, the Stargen hydrolysate supported comparable PHA synthesis characteristics as commercial glucose, with the strains Paraburkholderia sacchari and Burkholderia thailandensis performing best. During cultivation on 15 g L −1 glucose-equivalent concentration of the Stargen hydrolysate, the intracellular PHA content reached up to 48 % of the dry biomass and the PHA titer was around 2 g L −1 in shake flasks. Despite having higher protein content, the triple-enzyme hydrolysate yielded no obvious benefit compared to the Stargen treatment for growth or PHA synthesis. The results suggest that Stargen alone can effectively hydrolyze crude field pea starch, and the resulting hydrolysate is suitable for production of PHA biopolymers. To our knowledge, this is the first study producing PHA from field pea starch hydrolysates in submerged cultivation, highlighting a promising co-product strategy to support a sustainable and resilient plant protein sector.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it